Method for carrying out objective evaluation by utilizing dynamic software data and Python language

Abstract

The invention provides a method for carrying out objective evaluation by utilizing dynamic software data and a Python language. The method comprises the following steps: collecting and processing data; evaluation index and algorithm realization: designing a Python script to realize a corresponding evaluation index according to an actual operation condition and an analysis target of the vehicle, and performing quantitative evaluation according to different index algorithms by using data corresponding to the related evaluation index; wherein the evaluation indexes comprise the following four types: operation stability evaluation, drivability evaluation, cross-country evaluation and comfort evaluation; and the evaluation result is visualized. Data analysis is carried out through an algorithm, a consistent and standardized evaluation result can be provided, man-made subjective judgment interference is removed, and therefore the objectivity of evaluation is improved. The method is realized based on a Python language, and the system can be adjusted and expanded according to actual requirements.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a method for objectively evaluating by using dynamics software data and Python language. Background Art

[0002] With the rapid development of modern science and technology, the demand for objective evaluation of vehicle system dynamics behavior in the current automotive engineering field is also increasing. It is also a very important part of the automobile development process because it is an important basis for decision-making, design optimization and performance improvement.

[0003] Traditional methods are limited by the cumbersomeness of operation, limited data processing capabilities, and one-sided and biased subjective judgments, and cannot meet the evaluation requirements of high accuracy, high objectivity, high reliability, and high efficiency. Therefore, a more flexible and efficient evaluation method is needed to combine existing dynamic simulation tools and programming languages ​​to achieve a more objective and comprehensive evaluation. The excellent performance of the Python programming language in data processing capabilities, automated control, and rich library support has made it possible for data-driven decision optimization and evaluation method innovation. However, how to effectively integrate these with advanced data analysis technology to form a complete, efficient, objective, and highly integrated system evaluation method for multiple advanced technologies is still a challenge facing the current technical field. Summary of the invention

[0004] The purpose of the present invention is to provide a method for objective evaluation using kinetic software data and Python language to solve the technical problems mentioned in the background technology.

[0005] The technical solution adopted by the present invention to solve its technical problem is:

[0006] A method for objective evaluation using kinetic software data and Python language, comprising the following steps;

[0007] S01, data collection and processing;

[0008] S02, Evaluation indicators and algorithm implementation: According to the actual vehicle operating conditions and analysis objectives, design Python scripts to implement the corresponding evaluation indicators, use the corresponding data of relevant evaluation indicators, and perform quantitative evaluation according to different indicator algorithms. The implementation of specific algorithms combines the characteristics of the data and the analysis objectives, selects relevant vehicle theoretical algorithms, statistical methods, etc., to ensure the objectivity and practicality of the evaluation results;

[0009] S03. Visualization of evaluation results: Visual display of evaluation results, using Python graphics libraries (Matplotlib and Pyqtgraph) to generate data charts and reports, so as to intuitively display and analyze and explain the evaluation results; the visualization results include radar charts, trend charts, etc., and generate evaluation reports to help users understand the changing trends of data more clearly and provide strong support for decision-making. The evaluation report contains detailed information on data analysis, calculation results of evaluation indicators, scores of indicators with different weights, and graphical displays of corresponding indicators.

[0010] As a further technical solution of the present invention, the method further includes:

[0011] S04, System Integration and Automation: Integrate modules such as data collection, processing, evaluation and result display into a unified system to achieve fully automatic data processing and system indicator evaluation, provide a friendly interface, and allow users to select data, customize the evaluation indicator scoring range, set indicator weights, view evaluation results, etc. The system improves the accuracy and speed of data processing, reduces process intervention, and ensures the objectivity, standardization and automation of the evaluation process.

[0012] As a further technical solution of the present invention, in step S01, data collection and processing includes the following steps:

[0013] Use Python language scripts to automatically read the required data from the dynamics software API interface or fixed-format data files. The acquired data include but are not limited to time series data, system dynamic response data, mechanical property data, energy consumption data and control input, etc. The collected data are preprocessed through the data processing library (Pandas, NumPy and Scipy) in the Python programming language. The data preprocessing steps include format conversion, missing value processing, name mapping and data standardization, etc., to ensure the consistency and availability of the data, and facilitate subsequent processing and evaluation analysis.

[0014] As a further technical solution of the present invention, in step S02, the evaluation indicators of the evaluation system include the following four types: handling stability evaluation, drivability evaluation, off-road performance evaluation and comfort evaluation; wherein, the handling stability evaluation includes: steady-state steering characteristics, steering return performance, steering wheel characteristic test, steering transient response (steering wheel angle step input), steering transient response (steering wheel angle pulse input) and snake test; the drivability evaluation includes: consumption, performance, Tip-in, Tip-out, full throttle, zero throttle and gear shifting; the off-road performance evaluation includes: wheel contact resistance, four-wheel drive force distribution, electric drive force distribution, ramp performance, maneuverability; the comfort evaluation includes: random input and pulse input.

[0015] As a further technical solution of the present invention, in step S03, the evaluation results are visualized, and data charts and reports are generated using Python's graphics library to intuitively display and analyze and interpret the evaluation results; the visualization results include radar charts and trend charts, and an evaluation report is generated, which includes detailed information on the data analysis, calculation results of evaluation indicators, scores of indicators with different weights, and graphical displays of corresponding indicators.

[0016] The beneficial effects of the present invention are as follows: the present invention has high analysis efficiency and automation, and the data processing and evaluation process of the entire system is automated, which significantly improves the analysis efficiency, reduces manual data processing and analysis, and saves time and cost. Data analysis through algorithms can provide consistent and standardized evaluation results, remove interference from human subjective judgment, and thus improve the objectivity of the evaluation. Based on the Python language implementation, the system can be adjusted and expanded according to actual needs, such as updating evaluation indicators, adding evaluation algorithms, modifying data processing procedures, etc. The modular design of the system makes these adjustments quick and convenient, showing a high degree of flexibility and scalability. The formal display of charts and reports enables users to analyze, understand and use data more clearly, and provide support for data optimization design and decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A diagram showing an embodiment of the present invention.

[0018] Figure 2 A visualization diagram of the evaluation results provided in an embodiment of the present invention.

[0019] Figure 3 A system integration diagram provided for an embodiment of the present invention. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] The present invention involves the integration of technologies in multiple fields such as data processing, system simulation and automatic control, and proposes a method for comprehensive and objective evaluation by combining dynamics software data and Python language. This method achieves in-depth analysis and comprehensive evaluation of complex system behaviors by deeply integrating dynamics software data, Python programming language and data analysis technology, and provides powerful data support for scientific research, engineering design, economic analysis and other fields. As shown in the figure, the functional interface screenshot of the present invention (off-road performance) is as follows Figure 1 As shown, the functions and working processes of each part are as follows:

[0022] The embodiment of the present invention provides a method for objective evaluation using kinetic software data and Python language, comprising the following steps:

[0023] S01, data collection and processing;

[0024] S02, Evaluation indicators and algorithm implementation: According to the actual vehicle operating conditions and analysis objectives, design Python scripts to implement the corresponding evaluation indicators, use the corresponding data of relevant evaluation indicators, and perform quantitative evaluation according to different indicator algorithms. The implementation of specific algorithms combines the characteristics of the data and the analysis objectives, selects relevant vehicle theoretical algorithms, statistical methods, etc., to ensure the objectivity and practicality of the evaluation results;

[0025] S03. Visualization of evaluation results: Visual display of evaluation results, using Python graphics libraries (Matplotlib and Pyqtgraph) to generate data charts and reports, so as to intuitively display and analyze and explain the evaluation results; the visualization results include radar charts, trend charts, etc., and generate evaluation reports to help users understand the changing trends of data more clearly and provide strong support for decision-making. The evaluation report contains detailed information on data analysis, calculation results of evaluation indicators, scores of indicators with different weights, and graphical displays of corresponding indicators.

[0026] In this embodiment, the method further includes:

[0027] S04, System Integration and Automation: Integrate modules such as data collection, processing, evaluation and result display into a unified system to achieve fully automatic data processing and system indicator evaluation, provide a friendly interface, and allow users to select data, customize the evaluation indicator scoring range, set indicator weights, view evaluation results, etc. The system improves the accuracy and speed of data processing, reduces process intervention, and ensures the objectivity, standardization and automation of the evaluation process.

[0028] In step S01 of this embodiment, data collection and processing includes the following steps:

[0029] Use Python language scripts to automatically read the required data from the dynamics software API interface or fixed-format data files. The acquired data include but are not limited to time series data, system dynamic response data, mechanical property data, energy consumption data and control input, etc. The collected data are preprocessed through the data processing library (Pandas, NumPy and Scipy) in the Python programming language. The data preprocessing steps include format conversion, missing value processing, name mapping and data standardization, etc., to ensure the consistency and availability of the data, and facilitate subsequent processing and evaluation analysis.

[0030] In step S02 of the present embodiment, 1) the evaluation indicators of the evaluation system include the following four types: handling stability evaluation, drivability evaluation, off-road performance evaluation and comfort evaluation; wherein, the handling stability evaluation includes: steady-state steering characteristics, steering return performance, steering wheel characteristic test, steering transient response (steering wheel angle step input), steering transient response (steering wheel angle pulse input) and snake test; the drivability evaluation includes: consumption, performance, Tip-in, Tip-out, full throttle, zero throttle and gear shifting; the off-road performance evaluation includes: wheel contact, four-wheel drive force distribution, electric drive force distribution, ramp performance, maneuverability; the comfort evaluation includes: random input and pulse input.

[0031] 2) According to the above four types of analysis objectives and the actual operating conditions of the vehicle, determine the corresponding evaluation indicators, such as steady-state steering characteristics, lateral acceleration a at the neutral steering point n , understeer U and body roll K φ Evaluation: Wheel contact performance is evaluated according to contact pressure ratio and slope driving index;

[0032] 3) Design Python scripts to implement corresponding evaluation indicators by using NumPy for numerical calculations and array operations, Pandas for data processing and analysis, and SciPy for scientific computing and statistical analysis. According to different evaluation indicators, select appropriate data extraction methods to extract data related to the evaluation indicators from the preprocessed data;

[0033] 4) The implementation of specific algorithms is combined with the characteristics of the data and the analysis objectives, such as using the root mean square algorithm to calculate the root mean square value of the acceleration, and using the least squares method to calculate the lateral acceleration a of the neutral turning point according to the cubic polynomial fitting curve without constant terms. n , use the peak detection algorithm to calculate the peak value of acceleration, etc. At the same time, select relevant vehicle theory algorithms, such as dynamic models, handling models, etc.; statistical methods, such as calculating variance, standard deviation, spline interpolation, etc., to ensure the practicality and accuracy of the evaluation results;

[0034] 5) Scoring and optimizing evaluation algorithms: According to actual application requirements, the calculated index values ​​are scored and the evaluation algorithm is optimized to ensure the practicality of the evaluation results. The scoring formula is:

[0035]

[0036] Where: X min Lower limit, X max Upper limit value, X index value. The weight of the evaluation index and the index threshold range can be adjusted according to the specific usage scenario of the vehicle. Combine multiple evaluation indicators for comprehensive evaluation to ensure the comprehensiveness and objectivity of the evaluation results.

[0037] In order to enable those skilled in the art to understand more clearly, the present invention now provides the following specific embodiments;

[0038] A method for objective evaluation using kinetic software data and Python language, the method comprising the following specific steps:

[0039] Step 1: Collect vehicle off-road working condition data. Data can be read from the database and processed. Specifically, the following data are included: acceleration, cycle type, driving distance, front left steering angle, acceleration, frequency, front right steering angle, front left wheel load, front right wheel load, rear left wheel load, rear right wheel load, lateral acceleration, model switch, model time, roll angle, steering wheel angle, total mass, steering torque, vehicle speed, vertical acceleration, yaw speed, front left wheel speed, front left wheel torque, front right wheel speed, front right wheel torque, rear left wheel speed, rear left wheel torque, rear right wheel speed, rear right wheel torque, charging mode, gear position, throttle position, engine power, etc. The collected data is preprocessed through the data processing library (Pandas, NumPy and Scipy) in the Python programming language. The preprocessing steps include format conversion, missing value processing, name mapping and data standardization to ensure the consistency and availability of the data, which is convenient for subsequent processing and evaluation analysis.

[0040] Step 2: Evaluation index types include: 1. Handling stability evaluation: steady-state steering characteristics, steering return performance, steering wheel characteristic test, steering transient response (steering wheel angle step input), steering transient response (steering wheel angle pulse input), snake test; 2. Driving performance evaluation: consumption, performance, Tip-in, Tip-out, full throttle, zero throttle, shifting; 3. Off-road evaluation: wheel contact, four-wheel drive force distribution, electric drive force distribution, ramp performance, maneuverability; 4. Comfort evaluation: random input, pulse input. The system selects each indicator from step one according to the four types of evaluation indicators to calculate the required parameter values, and calculates the indicator value according to the corresponding indicator formula, such as: the pulse input of comfort selects Eva_VertiAccel vertical acceleration; according to the indicator algorithm, the NumPy library is used to quickly find the maximum vertical acceleration from the parameter value as the indicator value of the comfort pulse input, such as the indicator value is 9.832m / s / s; the scoring formula is used:

[0041] Where: X min The lower limit is 0m / s / s, X max The upper limit value is 31.44m / s / s, the X index value is 9.832m / s / s, and the weight is selected as the default value 1. The final score is 69 points, which is used as the index score of the comfort pulse input;

[0042] Step 3: Visualize all the indicator scores calculated in step 2 according to the indicator type, use Python graphics libraries (Matplotlib and Pyqtgraph) to generate data charts and reports, and intuitively display, analyze and explain the evaluation results, as follows Figure 2 As shown:

[0043] Step 4: Integrate data collection, processing, evaluation and result display modules into a unified system to achieve fully automatic data processing and comprehensive index evaluation. Display the comprehensive scores of four types of handling stability evaluation, driving performance evaluation, off-road performance evaluation and comfort evaluation, and select to display specific scoring indicators such as comfort indicators separately, as follows Figure 3 As shown;

[0044] The present invention can effectively and quickly score various specific performance index data of the vehicle with the actual performance. It significantly improves the analysis efficiency, reduces manual data processing and analysis, and saves time and cost. Through the algorithm for data analysis, it can provide consistent and standardized evaluation results, remove the interference of human subjective judgment, thereby improving the objectivity of the evaluation, and effectively integrate to form a complete, efficient, objective and highly integrated system evaluation of multiple advanced technologies. At the same time, the formal display of charts and reports enables users to analyze, understand and use data more clearly, provide support for data optimization design and decision-making, and enable non-professionals to quickly and intuitively understand vehicle performance, which has high practical application value.

[0045] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0046] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for objective evaluation using kinetic software data and Python language, characterized in that: The steps include: S01, data collection and processing; S02, evaluation index and algorithm implementation: according to the actual operating conditions of the vehicle and the analysis objectives, design a Python script to implement the corresponding evaluation index, use the corresponding data of the relevant evaluation index, and perform quantitative evaluation according to different index algorithms; the evaluation index includes the following four types: handling stability evaluation, drivability evaluation, off-road evaluation and comfort evaluation; S03. Visualization of evaluation results.

2. A method for objective evaluation using kinetic software data and Python language according to claim 1, characterized in that: The method further comprises: S04. System integration and automation: Integrate data collection, processing, evaluation and result display into a unified system to achieve fully automatic data processing and system indicator evaluation, provide a friendly interface, allow users to select data, customize the evaluation indicator scoring range, set indicator weights, and view evaluation results.

3. A method for objective evaluation using kinetic software data and Python language according to claim 1, characterized in that: In step S01, data collection and processing includes the following steps: Use Python language scripts to automatically read the required data from the dynamics software API interface or fixed-format data files. The acquired data includes but is not limited to time series data, system dynamic response data, mechanical property data, energy consumption data and control input. The collected data is preprocessed through the data processing library in the Python programming language. The data preprocessing steps include format conversion, missing value processing, name mapping and data standardization.

4. The method for objective evaluation using kinetic software data and Python language according to claim 1, characterized in that: In step S02, the evaluation indicators of the evaluation system include the following four types: handling stability evaluation, drivability evaluation, off-road performance evaluation and comfort evaluation; among them, the handling stability evaluation includes: steady-state steering characteristics, steering return performance, steering wheel characteristic test, steering transient response, steering transient response and snaking test; the drivability evaluation includes: consumption, performance, Tip-in, Tip-out, full throttle, zero throttle and gear shifting; the off-road performance evaluation includes: wheel contact, four-wheel drive force distribution, electric drive force distribution, ramp performance, maneuverability; the comfort evaluation includes: random input and pulse input.

5. The method for objective evaluation using kinetic software data and Python language according to claim 1, characterized in that: In step S03, the evaluation results are visualized, and data charts and reports are generated using Python's graphics library to intuitively display and analyze and interpret the evaluation results; the visualization results include radar charts and trend charts, and an evaluation report is generated. The evaluation report contains detailed information on the data analysis, calculation results of the evaluation indicators, scores of indicators with different weights, and graphical displays of the corresponding indicators.

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